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SIGMOD
2006
ACM
238views Database» more  SIGMOD 2006»
14 years 5 months ago
Continuous monitoring of top-k queries over sliding windows
Given a dataset P and a preference function f, a top-k query retrieves the k tuples in P with the highest scores according to f. Even though the problem is well-studied in convent...
Kyriakos Mouratidis, Spiridon Bakiras, Dimitris Pa...
IDA
2002
Springer
13 years 5 months ago
Online classification of nonstationary data streams
Most classification methods are based on the assumption that the data conforms to a stationary distribution. However, the real-world data is usually collected over certain periods...
Mark Last
ICDE
2007
IEEE
143views Database» more  ICDE 2007»
14 years 6 months ago
Hiding in the Crowd: Privacy Preservation on Evolving Streams through Correlation Tracking
We address the problem of preserving privacy in streams, which has received surprisingly limited attention. For static data, a well-studied and widely used approach is based on ra...
Feifei Li, Jimeng Sun, Spiros Papadimitriou, Georg...
ICDM
2005
IEEE
166views Data Mining» more  ICDM 2005»
13 years 11 months ago
An Algorithm for In-Core Frequent Itemset Mining on Streaming Data
Frequent itemset mining is a core data mining operation and has been extensively studied over the last decade. This paper takes a new approach for this problem and makes two major...
Ruoming Jin, Gagan Agrawal
DASFAA
2010
IEEE
193views Database» more  DASFAA 2010»
13 years 3 months ago
A Simple, Yet Effective and Efficient, Sliding Window Sampling Algorithm
Sampling streams of continuous data with limited memory, or reservoir sampling, is a utility algorithm. Standard reservoir sampling maintains a random sample of the entire stream a...
Xuesong Lu, Wee Hyong Tok, Chedy Raïssi, St&e...